curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
wan2.7-image
Generación y edición de imágenes wan2.7
- Serie de imágenes Wan2.7: admite text-to-image, edición de imágenes, edición interactiva, generación secuencial y referencia con múltiples imágenes
- Modo de procesamiento asíncrono: envíe una tarea y consulte los resultados usando el
task_iddevuelto - Admite resoluciones 1K / 2K / 4K; wan2.7-image-pro admite hasta 4K en text-to-image
- La facturación se basa en el número de imágenes generadas correctamente, independientemente de la resolución o la proporción
POST
/
v1
/
images
/
generations
curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
Autorización
string
requerido
Todas las solicitudes requieren autenticación mediante Bearer Token.Visite la página de gestión de claves de API para obtener su clave de API y, a continuación, añádala a la cabecera de la solicitud:
Authorization: Bearer YOUR_API_KEY
Modelos disponibles
| Modelo | Descripción | Resolución máx. (Text-to-Image) | Resolución máx. (Edición / Secuencial) | Precio |
|---|---|---|---|---|
wan2.7-image-pro | Edición profesional, mejores detalles, admite 4K | 4K | 2K | ¥0,50 / imagen |
wan2.7-image | Edición estándar, generación más rápida | 2K | 2K | ¥0,20 / imagen |
La facturación se basa en imágenes generadas correctamente × precio unitario. La entrada no se factura. La resolución y la proporción no afectan al precio. Las solicitudes fallidas no se cobran.
Cuerpo de la solicitud
string
requerido
Nombre del modelo de generación de imágenes.
wan2.7-image-pro— Edición profesional, hasta 4K en text-to-imagewan2.7-image— Edición estándar, más rápida, hasta 2K
boolean
predeterminado:"false"
Indica si se debe moderar el contenido antes de enviar la tarea de imagen.
true: revisar los prompts y las imágenes de entrada conomni-moderation-latestfalseu omitido: no enviar una solicitud de moderación, sin coste ni latencia de moderación adicionales (predeterminado)
string
Descripción textual para la generación de la imagen, hasta 5000 caracteres.
- Text-to-image (sin
image_urls): obligatorio - Edición de imágenes (con
image_urls): opcional pero recomendado
"A flower shop with exquisite windows, beautiful wooden door, flowers on display"array<string>
Array de URL de imágenes de entrada para escenarios de edición y referencia con múltiples imágenes.Al proporcionar este campo, la solicitud pasa al modo de edición de imágenes.Formatos admitidos: URL HTTP/HTTPS; Base64
data:image/...;base64,...Restricciones: hasta 9 imágenes; JPEG / PNG / WEBP / BMP; 240–8000 px, proporción 1:8 ~ 8:1; ≤ 20MB por imagenLa proporción de salida coincide automáticamente con la última imagen de entrada. El modo de edición admite solo hasta 2K; 4K no está disponible.
integer
predeterminado:"1"
Número de imágenes a generar.
- Modo estándar: 1–4 (predeterminado 1)
- Modo secuencial (
enable_sequential: true): 1–12 (predeterminado 1)
Se factura por cada imagen generada correctamente. Se precobra según
n.string
Resolución de salida o proporción. Admite tres formatos:① Palabra clave de resolución (recomendado):
1K / 2K (predeterminado) / 4K (solo para wan2.7-image-pro text-to-image)② Proporción: 1:1 / 16:9 / 9:16 / 4:3 / 3:4 / 3:2 / 2:3 (utiliza el nivel 2K por defecto)③ Dimensiones en píxeles: 1024x1024 o 1024*1024string
Palabra clave del nivel de resolución:
1K / 2K / 4K. Se puede combinar con size (proporción).| Modelo | Escenario | Niveles admitidos | Rango de píxeles |
|---|---|---|---|
wan2.7-image-pro | Text-to-image (no secuencial) | 1K / 2K / 4K | 768×768 ~ 4096×4096 |
wan2.7-image-pro | Edición / secuencial | 1K / 2K | 768×768 ~ 2048×2048 |
wan2.7-image | Todos los escenarios | 1K / 2K | 768×768 ~ 2048×2048 |
string
Prompt negativo que describe los elementos que se deben evitar. Ejemplo:
"blurry, distorted, low quality"boolean
predeterminado:"false"
Indica si debe añadirse una marca de agua “AI Generated” en la esquina inferior derecha.
integer
Semilla aleatoria, rango 0–2147483647. La misma semilla con parámetros idénticos produce resultados visualmente consistentes.
boolean
predeterminado:"true"
Activa el modo de razonamiento mejorado para mejorar la calidad de la imagen a costa de un mayor tiempo de generación.
Solo es efectivo cuando el modo secuencial está desactivado y no se proporciona ninguna imagen de entrada.
boolean
predeterminado:"false"
Activa el modo de generación secuencial de imágenes: genera múltiples imágenes coherentes temáticamente en una sola solicitud. Ideal para storyboards y series.
nmáximo es 12 cuando está activadothinking_modeycolor_palettese ignoran en modo secuencialwan2.7-image-proadmite hasta 2K en modo secuencial (no se admite 4K)
array
Cuadros delimitadores para edición interactiva: especifica las regiones exactas que se van a editar o donde se va a insertar contenido.Estructura:
[[[x1, y1, x2, y2], ...], ...]- La longitud del array externo debe coincidir con la de
image_urls - Pase
[]para las imágenes sin cuadro delimitador - Máximo 2 cuadros por imagen; las coordenadas son valores absolutos en píxeles, con origen (0,0) en la esquina superior izquierda
[[], [[989, 515, 1138, 681]]]array<object>
Paleta de colores personalizada. Solo en modo estándar (no en modo secuencial).
- 3–10 entradas (se recomiendan 8); cada entrada requiere
hexyratio - Todos los valores de
ratiodeben sumar exactamente100.00%
[
{ "hex": "#C2D1E6", "ratio": "23.51%" },
{ "hex": "#636574", "ratio": "76.49%" }
]
Respuesta
string
Estado de la respuesta. Devuelve
"success" en caso de éxito.array
Ejemplos
Texto a imagen (mínimo)
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
Texto a imagen (con resolución)
{
"model": "wan2.7-image-pro",
"prompt": "Summer beach, blue sky and white clouds, 4K ultra HD",
"size": "4K",
"thinking_mode": true
}
Texto a imagen (paleta de colores personalizada)
{
"model": "wan2.7-image-pro",
"prompt": "Minimalist modern living room",
"size": "2K",
"color_palette": [
{ "hex": "#C2D1E6", "ratio": "23.51%" },
{ "hex": "#CDD8E9", "ratio": "20.13%" },
{ "hex": "#B5C8DB", "ratio": "15.88%" },
{ "hex": "#C0B5B4", "ratio": "13.27%" },
{ "hex": "#DAE0EC", "ratio": "10.11%" },
{ "hex": "#636574", "ratio": "8.93%" },
{ "hex": "#CACAD2", "ratio": "5.55%" },
{ "hex": "#CBD4E4", "ratio": "2.62%" }
]
}
Generación secuencial de imágenes
{
"model": "wan2.7-image-pro",
"prompt": "Cinematic series: the same stray orange cat, consistent features. First: under cherry blossoms in spring. Second: old street shade in summer. Third: fallen leaves in autumn. Fourth: snow footprints in winter.",
"enable_sequential": true,
"n": 4,
"size": "2K"
}
Edición de una sola imagen
{
"model": "wan2.7-image",
"prompt": "Replace the background with a sunset scene, warm color tones",
"image_urls": ["https://example.com/portrait.jpg"],
"size": "2K"
}
Referencia con múltiples imágenes / fusión de elementos
{
"model": "wan2.7-image-pro",
"prompt": "Apply the graffiti from image 2 onto the car in image 1",
"image_urls": [
"https://example.com/car.webp",
"https://example.com/paint.webp"
],
"size": "2K"
}
Edición interactiva (cuadro delimitador)
bbox_list se corresponde uno a uno con image_urls. Pase [] para las imágenes sin selección.
{
"model": "wan2.7-image-pro",
"prompt": "Place the alarm clock from image 1 into the selected area of image 2, blending naturally",
"image_urls": [
"https://example.com/clock.webp",
"https://example.com/desk.webp"
],
"bbox_list": [
[],
[[989, 515, 1138, 681]]
],
"size": "2K"
}
Consulta de resultadosLa generación de imágenes es asíncrona. Consulte el endpoint Estado de la tarea utilizando el
task_id devuelto hasta que status == completed.